Total electricity generation dynamics analysis and renewable energy impacts in South Africa

IF 3.5 3区 工程技术 Q3 ENERGY & FUELS
Ntumba Marc-Alain Mutombo, Bubele Papy Numbi, Tahar Tafticht
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Abstract

This research explores the dynamics of total electricity generation (TEG) in South Africa through an analysis of data from the International Energy Agency database from 1990 to 2020. A comprehensive examination of various energy sources, including coal, oil, biofuels, nuclear, hydro, solar photovoltaic (PV), solar thermal, and wind, is conducted to ascertain their respective contributions to TEG. Employing the R software environment, the study employs a methodical analytical framework encompassing meticulous data preparation, statistical analysis, and model formulation. The data preparation phase involves intricate processes such as structuring, cleansing, and visualization aimed at eliminating stochastic variables and outliers. Missing data are addressed through the application of the Piecewise Cubic Hermite Interpolating Polynomial method. Subsequent statistical analyses are informed by tests for normality and homogeneity of variance, revealing deviations from normality and disparate variances across energy source groups. Consequently, non-parametric methodologies such as the Kruskal–Wallis test are adopted. Findings underscore the significant role of nuclear energy in TEG despite facing challenges. Model development entails the construction of multiple linear regression models with varying predictor sizes, with Model m06 emerging as the optimal choice, incorporating key predictors such as coal, nuclear, and solar PV. Rigorous diagnostic assessments confirm the robustness of Model m06 and its suitability for TEG prediction. Comparative analysis against actual data validates its superior performance, characterized by minimal errors and high predictive accuracy. The efficacy of Model m06 in capturing TEG dynamics underscores its utility for informing energy planning initiatives. Recommendations derived from the study advocate for prioritizing renewable energy integration, infrastructure investment, research endeavors, monitoring mechanisms, and public awareness campaigns to advance sustainable energy development goals in South Africa.

Abstract Image

南非总发电量动态分析和可再生能源的影响
本研究通过分析国际能源机构数据库中 1990 年至 2020 年的数据,探讨了南非总发电量(TEG)的动态变化。研究全面考察了各种能源,包括煤炭、石油、生物燃料、核能、水能、太阳能光伏发电(PV)、光热发电和风能,以确定它们各自对总发电量的贡献。本研究采用 R 软件环境,采用方法分析框架,包括细致的数据准备、统计分析和模型制定。数据准备阶段包括结构化、清理和可视化等复杂过程,旨在消除随机变量和异常值。缺失数据的处理采用了片断三次赫米特内插多项式方法。随后的统计分析采用了正态性和方差齐性检验,揭示了不同能源组之间的正态性偏差和方差差异。因此,采用了 Kruskal-Wallis 检验等非参数方法。研究结果表明,尽管面临挑战,核能在 TEG 中仍发挥着重要作用。模型开发需要构建具有不同预测因子大小的多元线性回归模型,其中模型 m06 是最佳选择,包含了煤炭、核能和太阳能光伏等关键预测因子。严格的诊断评估证实了 m06 模型的稳健性及其对 TEG 预测的适用性。与实际数据的对比分析验证了其卓越的性能,其特点是误差最小、预测准确性高。m06 模型在捕捉 TEG 动态方面的功效凸显了其在为能源规划计划提供信息方面的实用性。研究提出的建议主张优先考虑可再生能源整合、基础设施投资、研究工作、监测机制和公众宣传活动,以推进南非的可持续能源发展目标。
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来源期刊
Energy Science & Engineering
Energy Science & Engineering Engineering-Safety, Risk, Reliability and Quality
CiteScore
6.80
自引率
7.90%
发文量
298
审稿时长
11 weeks
期刊介绍: Energy Science & Engineering is a peer reviewed, open access journal dedicated to fundamental and applied research on energy and supply and use. Published as a co-operative venture of Wiley and SCI (Society of Chemical Industry), the journal offers authors a fast route to publication and the ability to share their research with the widest possible audience of scientists, professionals and other interested people across the globe. Securing an affordable and low carbon energy supply is a critical challenge of the 21st century and the solutions will require collaboration between scientists and engineers worldwide. This new journal aims to facilitate collaboration and spark innovation in energy research and development. Due to the importance of this topic to society and economic development the journal will give priority to quality research papers that are accessible to a broad readership and discuss sustainable, state-of-the art approaches to shaping the future of energy. This multidisciplinary journal will appeal to all researchers and professionals working in any area of energy in academia, industry or government, including scientists, engineers, consultants, policy-makers, government officials, economists and corporate organisations.
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